TY - JOUR A1 - Werner, Lennart A1 - Strohmeier, Michael A1 - Rothe, Julian A1 - Montenegro, Sergio T1 - Thrust vector observation for force feedback-controlled UAVs JF - Drones N2 - This paper presents a novel approach to Thrust Vector Control (TVC) for small Unmanned Aerial Vehicles (UAVs). The difficulties associated with conventional feed-forward TVC are outlined, and a practical solution to conquer these challenges is derived. The solution relies on observing boom deformations that are created by different thrust vector directions and high-velocity air inflow. The paper describes the required measurement electronics as well as the implementation of a dedicated testbed that allows the evaluation of mid-flight force measurements. Wind-tunnel tests show that the presented method for active thrust vector determination is able to quantify the disturbances due to the incoming air flow. KW - unmanned aerial vehicles KW - thrust vector control KW - force feedback Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262153 SN - 2504-446X VL - 6 IS - 2 ER - TY - JOUR A1 - Kaiser, Dennis A1 - Lesch, Veronika A1 - Rothe, Julian A1 - Strohmeier, Michael A1 - Spieß, Florian A1 - Krupitzer, Christian A1 - Montenegro, Sergio A1 - Kounev, Samuel T1 - Towards Self-Aware Multirotor Formations JF - Computers N2 - In the present day, unmanned aerial vehicles become seemingly more popular every year, but, without regulation of the increasing number of these vehicles, the air space could become chaotic and uncontrollable. In this work, a framework is proposed to combine self-aware computing with multirotor formations to address this problem. The self-awareness is envisioned to improve the dynamic behavior of multirotors. The formation scheme that is implemented is called platooning, which arranges vehicles in a string behind the lead vehicle and is proposed to bring order into chaotic air space. Since multirotors define a general category of unmanned aerial vehicles, the focus of this thesis are quadcopters, platforms with four rotors. A modification for the LRA-M self-awareness loop is proposed and named Platooning Awareness. The implemented framework is able to offer two flight modes that enable waypoint following and the self-awareness module to find a path through scenarios, where obstacles are present on the way, onto a goal position. The evaluation of this work shows that the proposed framework is able to use self-awareness to learn about its environment, avoid obstacles, and can successfully move a platoon of drones through multiple scenarios. KW - self-aware computing KW - unmanned aerial vehicles KW - multirotors KW - quadcopters KW - intelligent transportation systems Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-200572 SN - 2073-431X VL - 9 IS - 1 ER -